![]() He didn’t start with a plan for the song he just started fiddling and experimenting and the band developed it from there. Take Paul McCartney, who came up with the track “ Get Back” during a jam session. DALL-E 2 does seem to shortcut this process entirely: you have an idea and type it in, and you’re done.īut when I paint the old-fashioned way, I’ve found that my paintings come from the exploratory process, not just from executing my initial goals. The artist intended to show a thing, or express an emotion, and so they made this image. ![]() Today the human authorship and craft involved in artistic photography are recognized, and critics understand that the best photography involves much more than just pushing a button.Įven so, we often discuss works of art as if they directly came from the artist’s intent. But in my view, this line of thinking echoes the classic take that photography cannot be art because a machine did all the work. You might be inclined to say there’s little artistic merit in an image produced by a few keystrokes. If these images succeed as art, they are products of how the algorithm was designed, the images it was trained on, and – most importantly – how artists use it. Even though it sometimes feels like magic, under the hood it is still a computer algorithm, rigidly following instructions from the algorithm’s authors at OpenAI. If someone told you that a person made all these images, of course you’d say they were creative.īut this does not make DALL-E 2 an artist. In fact, no human can do what DALL-E 2 does: create such a high-quality, varied range of images in mere seconds. Then I realized that it is, in a way, a better painter than I am. I had a moment early on while using DALL-E 2 to generate different kinds of paintings, in all different styles – like “ Odilon Redon painting of Seattle” – when it hit me that this was better than any painting algorithm I’ve ever developed. It’s easy to imagine these tools transforming the way people make images and communicate, whether via memes, greeting cards, advertising – and, yes, art. Google Research recently announced an impressive, similar text-to-image system, and one independent developer is publicly developing their own version that anyone can try right now on the web, although it’s not yet as good as DALL-E or Google’s system. In principle, anyone with enough resources and expertise can make a system like this. And, sometimes, the unexpected results are the best. ![]() But, even with the need to sift through many outputs or try different text prompts, there’s no other existing way to pump out so many great results so quickly – not even by hiring an artist. Not all of the images will look pleasing to the eye, nor do they necessarily reflect what you had in mind. Each set of images takes less than a minute to generate. It’s staggering that an algorithm can do this. They gathered some of the images online and licensed others. OpenAI researchers built DALL-E 2 from an enormous collection of images with captions. It also raises questions about what it means to be creative when DALL-E 2 seems to automate so much of the creative process itself. It raises immediate questions about how these technologies will change how art is made and consumed. After hours of experimentation, it’s clear that DALL-E – while not without shortcomings – is leaps and bounds ahead of existing image generation technology. But a small and growing number of people – myself included – have been given access to experiment with it.Īs a researcher studying the nexus of technology and art, I was keen to see how well the program worked. The program, which was announced by the artificial intelligence research laboratory OpenAI in April 2022, hasn’t been released to the public. A picture may be worth a thousand words, but thanks to an artificial intelligence program called DALL-E 2, you can have a professional-looking image with far fewer.ĭALL-E 2 is a new neural network algorithm that creates a picture from a short phrase or sentence that you provide.
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